Abstract: Face detection in a spherical image is performed using overcapture. Multiple views of a spherical image are separately processed using face detection, and results of the face detection for those views are projected to a format for further processing of the spherical image.

Abstract: Auto exposure metering is adapted for spherical panoramic content. Using input image data, a first metering map is generated for a selected image sensor and a second metering map is generated for an unselected image sensor. Auto exposure level values for the selected image sensor and for the unselected image sensor are respectively metered using the first metering map and the second metering map, such as by adjusting luminance weights in certain locations of the respective image sensor panoramic image capture band. Hemispherical images are processed using the auto exposure metered level values and stitched together in a panoramic format to produce a spherical panoramic image. The metering maps are generated to account for areas of greatest image data importance relative to a primary orientation direction of the spherical panoramic image. This allows for effective auto exposure metering of such areas within the resulting spherical panoramic image.

Abstract: An image capture device may obtain first frames at a first frame rate from a first image sensor and obtain second frames at a second frame rate from a second image sensor. The image capture device may process the first frames from the first image sensor and store the processed first frames in a memory. The image capture device may partially process the second frames from the second image sensor to obtain first camera control statistics. The image capture device may switch a capture mode to obtain third frames at the second frame rate from the first image sensor obtain fourth frames at the first frame rate from the second image sensor.

Abstract: An image capture device may obtain first frames at a first frame rate from a first image sensor and obtain second frames at a second frame rate from a second image sensor. The image capture device may process the first frames from the first image sensor and store the processed first frames in a memory. The image capture device may partially process the second frames from the second image sensor to obtain first camera control statistics. The image capture device may switch a capture mode to obtain third frames at the second frame rate from the first image sensor obtain fourth frames at the first frame rate from the second image sensor.

Abstract: An image capture device may capture two hemispherical views of a scene. The two hemispherical view of the scene may be stitched along a stitch line. The image capture device may be rotated to align the stitch line with a mid-line of a panoramic field of view of the scene. Separate exposure settings may be used to capture the two hemispherical views of the scene, with the exposure settings increasing the dynamic range of the scene depicted within the panoramic field of view of the scene. The panoramic field of view of the scene may be punched out as panoramic visual content.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include accessing an image from an image sensor; detecting an object area on the image; classifying the object area on the image; applying a filter to an object area of the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: An image capture apparatus may include an image sensor, a motion sensor, and an auto-exposure unit. The auto-exposure unit may obtain an input image captured during an exposure interval and corresponding motion data indicating motion of the image capture apparatus during the exposure interval. The auto-exposure unit may obtain image information-amount data for the input image. The auto-exposure unit may obtain derivative information-amount data based on the information-amount data and a candidate exposure adjustment. The auto-exposure unit may obtain an information-amount maximizing exposure interval based on the information-amount data and the derivative information-amount data. The image capture apparats may control the image sensor to obtain a subsequent input image signal representing a subsequent input image captured during the information-amount maximizing exposure interval, and output or store information representing the subsequent input image.

Abstract: An image capture device may capture two hemispherical views of a scene. The two hemispherical view of the scene may be stitched along a stitch line. The image capture device may be rotated to align the stitch line with a mid-line of a panoramic field of view of the scene. Separate exposure settings may be used to capture the two hemispherical views of the scene, with the exposure settings increasing the dynamic range of the scene depicted within the panoramic field of view of the scene. The panoramic field of view of the scene may be punched out as panoramic visual content.

Abstract: Multiple lookup tables (LUTs) storing different numbers of control point values are used to process pixels within different blocks of an image, such as after image processing using tone mapping and/or tone control, and/or to collect histogram information or implement 3D LUTs. First control point values stored within a first LUT are applied against pixels of a given block of an image to produce a distorted image block. Second control point values stored within a second lookup table are applied against a pixel of the distorted image block to produce a processed pixel. The second LUT is one of a plurality of second LUTs and stores fewer values than the first LUT. A processed image is produced using the processed pixel. The processed image is then output for further processing or display.

Abstract: Methods for auto white balance (AWB) processing are described herein. An image capture device includes a first image capture device to capture a first image, a second image capture device to capture a second image, and an image signal processor. The image signal processor is configured to generate a global AWB scale based on the first image and the second image, apply a first image capture device calibration factor to the global AWB scale to generate a first image capture device AWB scale, apply a second image capture device calibration factor to the global AWB scale to generate a second image capture device AWB scale, compensate the first image using the first image capture device AWB scale, compensate the second image using the second image capture device AWB scale, and output an image based on the compensated first image and compensated second image.

Abstract: Methods for parameter alignment processing are described herein. An image capture device includes a first image capture device configured to capture a first image, a second image capture device configured to capture a second image, and an image signal processor connected to the first image capture device and to the second image capture device. The image signal processor is configured to apply, to the first image and the second image, at least two of a respective luminance lens shading (LLS) compensation factor, a respective color lens shading (CLS) compensation factor, a respective exposure difference compensation factor, a respective white balance compensation factor, a respective lens exposure correction (LEC) compensation factor, and a respective flare compensation factor, blend the compensated first image and the compensated second image to form a blended image, and output an image based on the blended image.

Abstract: An image capture device may include an image sensor, a processor, and a memory. The image sensor may be configured to obtain an image. The processor may be configured to generate a grid on the image. The grid may include one or more vertices. The one or more vertices may be used to form tiles. The processor may be configured to determine a flare level of each vertex. The processor may be configured to assign a maximum flare level for each tile of the image. The processor may be configured to sort the tiles. The tiles may be sorted based on the maximum flare level of each tile. The processor may be configured to apply a flare compensation to a subset of the tiles to obtain a processed image. The processed image may have reduced flare artifacts or no flare artifacts. The processed image may be stored in the memory.

Abstract: Auto exposure processing for spherical images improves image quality by reducing visible exposure level variation along a stitch line within a spherical image. An average global luminance value is determined based on auto exposure configurations of first and second image sensors. Delta luminance values are determined for each of the image sensors based on the average global luminance value and a luminance variance between the image sensors. The auto exposure configurations of the image sensors are then updated using the delta luminance values, and the updated auto exposure configurations are used to capture images which are then combined to produce the spherical image. In some cases wherein updating the auto exposure configurations using the delta luminance values would breach a threshold representing a target luminosity for the scene, the use of the delta luminance values may be limited or those values may instead be discarded.

Abstract: Image analysis and processing may include a first sensor readout unit configured to receive first Bayer format image data, a second sensor readout unit configured to receive second Bayer format image data, a first Bayer-to-RGB unit configured to obtain first RGB format image data based on the first Bayer format image data, a second Bayer-to-RGB unit configured to obtain second RGB format image data based on the second Bayer format image data, a high dynamic range unit configured to obtain high dynamic range image data based on a combination of the first RGB format image data and the second RGB format image data, an RGB-to-YUV unit configured to obtain YUV format image data based on the high dynamic range image data, and a three-dimensional noise reduction unit configured to obtain noise reduced image data based on the YUV format image data.

Abstract: Multiple lookup tables (LUTs) storing different numbers of control point values are used to process pixels within different blocks of an image, such as after image processing using tone mapping and/or tone control, and/or to collect histogram information or implement 3D LUTs. First control point values stored within a first LUT are applied against pixels of a given block of an image to produce a distorted image block. Second control point values stored within a second lookup table are applied against a pixel of the distorted image block to produce a processed pixel. The second LUT is one of a plurality of second LUTs and stores fewer values than the first LUT. A processed image is produced using the processed pixel. The processed image is then output for further processing or display.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include accessing an image from an image sensor; detecting an object area on the image; classifying the object area on the image; applying a filter to an object area of the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: Image analysis and processing may include using an image processor to receive image data corresponding to an input image, determine an initial gain value for the image data based on at least one of a two-dimensional gain map or a parameterized radial gain model, determine whether the initial gain value is below a threshold, determine a maximum RGB triplet value for the image data where the initial gain value is below the threshold, determine a pixel intensity as output of a function for saturation management, determine a final gain value for the image data based on the maximum RGB triplet value and the pixel intensity, apply the final gain value against the image data to produce processed image data, and output the processed image data for further processing using the image processor.

Abstract: Image analysis and processing may include a multiple-tone-control (MTC) unit configured to obtain a tone-control gain lookup table, a plurality of MTC gain lookup tables, wherein the input image is divided into a plurality of blocks and wherein the plurality of MTC gain lookup tables includes a respective MTC gain lookup table corresponding to each respective block from the plurality of blocks, MTC grid parameters, MTC weighting parameters, a tone-control gain based on the tone-control gain lookup table, a MTC gain based on at least one MTC gain lookup table from the plurality of MTC gain lookup tables, the MTC grid parameters, and the MTC weighting parameters, and an output value based on the tone-control gain and the MTC gain.

Abstract: Image signal processing includes obtaining two or more image signals from a first hyper-hemispherical image sensor, where each of the two or more image signals has a different exposure and obtaining two or more image signals from a second hyper-hemispherical image sensor, where each of the two or more image signals has a different exposure. Image signal processing includes generating an exposure compensated image based on a gain value applied to an exposure level of a first image and a gain value applied to an exposure level of a second image. Image signal processing further includes performing high dynamic range (HDR) processing on the exposure compensated image. The HDR processing may be performed on a high a frequency portion of the exposure compensated image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a current image of a sequence of images from an image sensor; combining the current image with a recirculated image to obtain a noise reduced image, where the recirculated image is based on one or more previous images of the sequence of images from the image sensor; determining a noise map for the noise reduced image, where the noise map is determined based on estimates of noise levels for pixels in the current image, a noise map for the recirculated image, and a set of mixing weights; recirculating the noise map with the noise reduced image to combine the noise reduced image with a next image of the sequence of images from the image sensor; and storing, displaying, or transmitting an output image that is based on the noise reduced image.